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MyOperator

Site Reliability Engineer

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  • Posted 7 hours ago
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Job Description

About MyOperator

MyOperator is a Business AI Operator platform that enables businesses, teams, and AI agents to work together seamlessly for customer operations such as Sales, Support, Escalations, Feedback, and Refund processes. With 12,000+ businesses using our platform, we operate at meaningful scale and power mission-critical communication workflows including voice bots, WhatsApp automation, and intelligent call routing.

We are building for reliability, speed, and impact. MyOperator values ownership, critical thinking, and execution. This is a high-expectation, high-learning environment where engineers are empowered to solve complex problems and build systems that directly affect customer outcomes.

Role Overview

We are looking for a skilled and proactive Site Reliability Engineer (SRE) to take end-to-end ownership of production reliability, observability, and performance engineering across MyOperator's AI-powered communication infrastructure.

This role is not operational-only — it requires strong system design thinking, deep troubleshooting ability, and a production ownership mindset. You will define reliability standards, build observability frameworks, lead incident response, and drive SLO-based engineering practices across distributed AWS and Kubernetes environments.

Key Responsibilities

  • Own production reliability, uptime, latency, and error budgets across critical services.
  • Design and manage production-grade monitoring using Grafana, VictoriaMetrics (Prometheus), and AWS CloudWatch.
  • Define and enforce SLIs, SLOs, and SLA thresholds for AI communication systems (voice bots, WhatsApp APIs, call routing).
  • Build real-time operational dashboards for incident response, capacity planning, and leadership visibility.
  • Implement end-to-end distributed tracing using OpenTelemetry (OTEL Collector).
  • Design and maintain centralized logging with strong correlation between logs, metrics, and traces.
  • Create SLO-based alerting systems with minimal noise and fast incident detection.
  • Lead incident response lifecycle: alert triage, mitigation, RCA documentation, and preventive improvements.
  • Drive MTTR reduction through structured monitoring, automation, and reliability engineering practices.
  • Monitor and troubleshoot AWS EKS (Kubernetes) production workloads.
  • Instrument and monitor LLM API integrations, AI inference pipelines, and messaging systems.
  • Analyze logs using OpenSearch / ELK for anomaly detection and root cause identification.
  • Automate operational workflows using Python or Bash to eliminate manual toil.
  • Drive performance optimization, scalability improvements, and capacity planning.
  • Collaborate with engineering teams to instrument new services from day one.

Required Skills & Qualifications

  • 3–6 years of experience in Site Reliability Engineering, DevOps, or Platform Engineering roles.
  • Hands-on experience with:
  1. VictoriaMetrics / Prometheus (time-series monitoring)
  2. Grafana dashboards and visualization
  3. PromQL for writing complex queries and alerts
  • Experience implementing distributed tracing using OpenTelemetry (Mandatory).
  • Strong experience with centralized logging systems (ELK / OpenSearch / Loki).
  • Experience with alerting frameworks such as Alertmanager or Grafana Alerts.
  • Strong understanding of SLIs, SLOs, SLA design, and reliability engineering principles.
  • Hands-on experience managing AWS production workloads (EC2, RDS, ELB, CloudWatch, IAM).
  • Experience with Kubernetes (AWS EKS preferred).
  • Good understanding of Linux systems, networking, and cloud infrastructure.
  • Experience handling production incidents and participating in on-call rotations.
  • Ability to automate operational tasks using Python or Bash.

Good to Have

  • Experience with OpenSearch / ELK log pipelines and anomaly detection.
  • Kubernetes monitoring (pod health, node metrics, autoscaling behavior).
  • CI/CD observability integration (Jenkins, GitHub Actions).
  • Experience monitoring LLM APIs and AI inference pipelines.
  • Familiarity with MLOps or AI observability tools (Arize, WhyLabs, etc.).
  • Service mesh exposure (Istio).
  • Infrastructure as Code (Terraform, CloudFormation).
  • Experience with chaos engineering or load testing tools.
  • Multi-cluster or multi-region architecture exposure.

Key Expectations

  • Ownership of production systems and high availability.
  • Strong troubleshooting and debugging skills.
  • Focus on automation and reliability improvements.
  • Proactive approach to incident prevention.
  • Ability to reduce alert noise and improve signal quality.
  • Data-driven approach to reliability engineering.

This Role Is Not For

  • Candidates with purely development experience and no production ownership.
  • Candidates without real incident response or on-call experience.
  • Freshers or candidates with less than 3 years of experience.

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About Company

Job ID: 145568311